ABSTRACT
Interactive models of language processing assume that information flows both bottom-up and top-down, so that the representations formed at each level may be influenced by higher as well as lower levels. I describe a framework called the interactive activation framework that embeds this key assumption among others, including the assumption that influences from different sources are combined nonlinearly. This nonlinearity means that information that may be decisive under some circumstances may have little or no effect under other conditions. Two attempts to rule out an interactive account in favour of models in which individual components of the language processing system act autonomously are considered in the light of the interactive activation framework. In both cases, the facts are as expected from the principles of interactive activation. In general, existing facts do not rule out an interactive account, but they do not require one either. To demonstrate that more definitive tests of interaction are possible, I describe an experiment that demonstrates a new kind of influence of a higher-level factor (lexical membership) on a lower level of processing (phoneme identification). The experiment illustrates one reason why feedback from higher levels is computationally desirable; it allows lower levels to be tuned by contextual factors so that they can supply more accurate information to higher levels.
